Octane Number Research Articles

Effects of Dimethyl Ether and Propane Blends on Knocking Behavior in a Boosted SI Engine

<div>Dimethyl ether (DME) is an alternative fuel that, blended with propane, could be an excellent alternative for exploring the use of fuels from renewable sources. DME–propane blends are feasible for their comparable physicochemical properties; these fuels may be pressured as liquids using moderate pressure at ambient temperature. Adding a proportion of DME with a low octane number to a less reactive fuel like propane can improve the combustion process. However, the increased reactivity of the mixture induced by the DME could lead to the early appearance of knocking, and this tendency may even be pronounced in boosted SI engines. Hence, this study experimentally analyzes the effect of E10 gasoline (baseline) and DME–propane blends, with varying proportions of DME in propane ranging from 0% to 30% by weight, in increments of 5% on knocking tendency, combustion characteristics, gaseous emissions, and particle number concentration, under different intake pressure conditions (0.8, 0.9, 1.0, and 1.1 bar) in an SI engine. The results show that as the proportion of DME in the propane blend rises, the knocking tendency becomes more pronounced. That behavior intensifies with increasing intake pressure, but with 20% DME in the propane blend, reaching the maximum brake torque (MBT) without knocking in the four boosted conditions is feasible. The presence of knock limited the advance of combustion phasing and decreased the gross indicated thermal efficiency (ITEg) with E10 gasoline and 25% and 30% DME in propane blends under 1.0 and 1.1 bar boosted conditions. In these knock-limited circumstances, the NOx emissions decreased due to the retarded phasing, and THC and PN emissions increased due to the lower combustion stability, considerably raising the concentration of accumulation mode particles in the particle size distribution (PSD) compared to the other fuel blends tested.</div>

Influence of γ-Fe2O3 Nanoparticles Added to Gasoline–Bio-Oil Blends Derived from Plastic Waste on Combustion and Emissions Generated in a Gasoline Engine

The environmental pressure to reduce the use of fossil fuels such as gasoline generates the need to search for new fuels that have similar characteristics to conventional fuels. In this sense, the objective of the present study is the use of commercial gasoline in mixtures with pyrolytic oil from plastic waste and the addition of γ-Fe2O3 nanoparticles (NPs) in a spark ignition engine to analyze both the power generated in a real engine and the emissions resulting from the combustion process. The pyrolytic oil used was obtained from thermal pyrolysis at low temperatures (450 °C) of a mixture composed of 75% polystyrene (PS) and 25% polypropylene (PP), which was mixed with 87 octane commercial gasoline in 2% and 5% by volume and 40 mg of γ-Fe2O3 NPs. A standard sample was proposed, which was only gasoline, one mixture of gasoline with bio-oil, and a gasoline, bio-oil, and NPs mixture. The bio-oil produced from the pyrolysis of PS and PP enhances the octane number of the fuel and improves the engine’s power performance at low revolutions. In contrast, the addition of iron NPs significantly improves gaseous emissions with a reduction in emissions of CO (carbon monoxide), NOx (nitrogen oxide), and HCs (hydrocarbons) due to its advantages, which include its catalytic effect, presence of active oxygen, and its large surface area.

CONVERSİON OF n-HEXANE OVER CATALYSTS BASED ON SULFATED ZIRCONIUM DIOXIDE

The isomerization process is becoming increasingly important in the modern petroleum refining context due to the limitations on the content of benzene, aromatic compounds, and olefins in gasoline. Isomerization is an effective and profitable process for octane enhancement of gasoline unlike other octane increasing processes. Due to the low sulfur and benzene content, the isomerate can be used as an ideal blending gasoline component. Therefore, the isomerization process has a great importance in petroleum refineries to increase the fuel octane number. This article aimed to study the conversion process of normal hexane over palladium and platinum containing catalysts on the base of sulfated zirconium dioxide. It has been determined that due to their high-performance characteristics, catalytic systems based on sulfated zirconium dioxide can be considered the most promising for isomerization of normal alkanes. Moreover, comparison of palladium-containing catalysts based on sulfated zirconium dioxide with platinum-containing catalysts based on sulfated zirconium dioxide showed that palladium sulfated zirconia catalysts have high catalytic performance in the isomerization of normal hexane. Keywords: alkanes, catalyst, platinum, palladium, isomerization, temperature, sulfated zirconium dioxide. .

Reaction network design and hybrid modeling of S Zorb

At present, many countries are becoming more and more stringent in terms of sulfur content in fuel oil. S Zorb is a kind of desulfurization technology with advantages of exceptional desulfurization efficiency and small impact on octane number. To meet the needs of environmental requirements and the trend of digitalization in the petrochemical industry, a first-principle model of S Zorb was established based on industry data. In order to describe the desulfurization and the other side reactions, a reaction network was designed and the kinetic parameters were estimated by the particle swarm optimization algorithm. Two hybrid models based on the first-principle model and support vector regression method were established to correct the mass fraction of sulfur and predict the research octane number of the refined gasoline respectively. The results indicate that the hybrid models can predict the mass fraction of PIONA, sulfur content and research octane number of the refined gasoline accurately, of which the mean absolute percentage errors are less than 6%. Hybrid models were then applied to optimize the decision variables to minimize the research octane number loss. Optimization results show that the average reduction of the loss of research octane number is 21.8%, which suggests that the models developed hold promise for guiding practical production.

Jerusalem Artichoke as a Raw Material for Manufacturing Alternative Fuels for Gasoline Internal Combustion Engines

The Jerusalem artichoke (Helianthus tuberosus) is a high-yield crop, and a great source of fermentable sugars, which gives the plant the potential to be used as raw material for economical fuel alcohol production. In this article, the authors focus on the technological aspect of the biofuel manufacturing process and its properties. First, the fuel alcohol manufacturing process is described, afterwards assessing its characteristics such as kinematic viscosity, density and octane number. The amount of fuel alcohol obtained from 10 kg of biomass equals to 0.85 L. Afterwards, the mixtures of gasoline and obtained fuel alcohol are prepared and studied. Optimal alcohol and gasoline mixtures are determined to obtain biofuels with octane ratings of 92, 95 and 98. The kinematic viscosity of obtained mixtures does not differ significantly from its values for pure gasoline. The obtained biofuel mixture with 25% alcohol content yielded a decrease of sulfur content by 38%, an increase of vaporized fuel amount by 17.5% at 70 °C and by 10.5% at a temperature of 100 °C, which improves engine startup time and ensures its stable operation in comparison to pure gasoline. The alcohol obtained can be successfully used as a high-octane additive for gasolines.

Prediction and optimisation of gasoline quality in petroleum refining: The use of machine learning model as a surrogate in optimisation framework

AbstractHardware‐based sensing frameworks such as cooperative fuel research engines are conventionally used to monitor research octane number (RON) in the petroleum refining industry. Machine learning techniques are employed to predict the RON of integrated naphtha reforming and isomerisation processes. A dynamic Aspen HYSYS model was used to generate data by introducing artificial uncertainties in the range of ±5% in process conditions, such as temperature, flow rates, etc. The generated data was used to train support vector machines (SVM), Gaussian process regression (GPR), artificial neural networks (ANN), regression trees (RT), and ensemble trees (ET). Hyperparameter tuning was performed to enhance the prediction capabilities of GPR, ANN, SVM, ET and RT models. Performance analysis of the models indicates that GPR, ANN, and SVM with R2 values of 0.99, 0.978, and 0.979 and RMSE values of 0.108, 0.262, and 0.258, respectively performed better than the remaining models and had the prediction capability to capture the RON dependence on predictor variables. ET and RT had an R2 value of 0.94 and 0.89, respectively. The GPR model was used as a surrogate model for fitness function evaluations in two optimisation frameworks based on genetic algorithm and particle swarm method. Optimal parameter values found by the optimisation methodology increased the RON value by 3.52%. The proposed methodology of surrogate‐based optimisation will provide a platform for plant‐level implementation to realise the concept of industry 4.0 in the refinery.

Fingerprinting of Octane Rating Gasoline and its Contaminants Using Synchronous Fluorescence Spectroscopy.

Fuel fraud has proliferated due to underlying economic advantage in nearly every nation. For the purpose of detecting adulteration and providing real-time quality assurance, non-destructive oil analysis is crucial. This paper reports the simple approach for fingerprinting undiluted petroleum products including gasoline from various brands, diesel, and kerosene oil in comparison with organic solvents using synchronous fluorescence spectroscopy and hierarchical cluster analysis. Fluorescence-based successful detection of adulterated samples is demonstrated in imported RON 92 gasoline, synthetically adulterated with kerosene oil (KO) in proportions up to 70%. Compared to gasoline, kerosene oil has a lower relative poly aromatic hydrocarbons, as the amount of kerosene oil (KO) increases, the KO peak at 352nm rises, but the gasoline's peak intensity decreases in the range of 371-500nm. It is noteworthy that imported fuel grades RON 92 and RON 95 are comparable to each other and surprisingly clustered with RON 91 from the Attock refinery presenting concerns about quality. Similarly, the Shell website mentions that Shell V-Power is RON 99 but interestingly it clusters with retail fuel samples acquired from PSO filling stations and PSO RON 95 showing disagreement with the claim that the fuel is high octane. Another use for this technique in oil exploration was the detection of adulterants and successfully spotted methanol, ethanol, and kerosene oil in the tainted samples. These findings suggest SFS as an accurate, and low-cost testing tool for gasoline fingerprinting and contamination screening.

Machine learning-based screening of fuel properties for SI and CI engines using a hybrid group extraction method

The design of high-performance fuels is crucial for achieving clean and efficient combustion of engines. In the current study, a framework for machine learning (ML) model-based fuel design is presented to identify compounds with desired properties for internal combustion engine (ICE) applications. Descriptors computed from newly proposed structural and positional-based group extraction method in this study are used as input in ML models due to the simplicity and computational-efficiency. The ML models were trained and validated using publically available experimental data for up to 1135 compounds. The results demonstrated a high level of predictive accuracy, with R2 values generally exceeding 0.99 for 11 physicochemical properties including melting point, boiling point, enthalpy of vaporization, surface tension, dynamic viscosity, low heating value, liquid density, yield sooting index, cetane number, research octane number and motor octane number. Furthermore, by employing the developed ML models to predict new data, a Fuel Property Database containing 1135 fuels with 12 fuel properties is established, enhanced by an interface for a user-friendly Fuel Physicochemical Properties Prediction Tool that facilitates swift property predictions and database expansion. The Pearson correlation coefficient (PCC) approach is subsequently employed to assess the correlation between descriptors and predicted or experimental properties. The strong agreement between the correlations affirms the effective predictive performance of the ML models within the calibrated data range. Additionally, a PCC analysis is conducted to reveal the individual effects of influential factors and their interactions, highlighting significant features like molecular weight size, degree of branching, and functional group content that influence physical and chemical properties, thereby providing valuable insights for fuel design and optimization. Finally, a initial comprehensive data-driven screening was carried out to identify potential fuel candidates that meet the key property limits for combustion applications in both spark-ignition (SI) and compression-ignition (CI) engines.

APPLICATION OF ATOMIC OXYGEN FOR GASOLINE OCTANE NUMBER DETERMINATION

There is a method that measures the thermal effect of a low-temperature oxidation reaction to determine the octane number of gasoline. The reaction was conducted in the presence of ozone on a thermistor surface at a temperature of the vapor-gas mixture equal to the end boiling point of gasoline in order to lower the analysis temperature. Keywords: low-temperature oxidation, atomic oxygen, gasoline, detonation resistance, octane number, ozone, and thermistor.

Isomerization performance of n-hexane in hydrogen atmosphere over the multistage porous composite NixPy-MCM-41/MOR catalyst

With the increasingly strict environmental protection requirements and the continuous improvement for the performance of clean fuel, it is imperative to develop technology for producing high octane gasoline blending components. Alkane isomerization was one of the important ways due to it contain little olefin and aromatic components which are harmful to the environment. In this study, the multistage porous composite NixPy-MCM-41/MOR catalysts were synthesized in the hydrogen atmosphere, the conversion rate and selectivity of n-hexane hydrogen isomerization with different conditions was tested in a fixed bed reactor. The results shown that the loading volume of active components is 4.0 wt%, nickel-phosphorus ratio of 0.5, reaction temperature of 250 °C, reaction pressure 3.0 MPa and volume space velocity is 2.0 h−1 with the hydrogen condition showed good catalytic activity for the n-hexane isomerization. The conversion rate of n-hexane is 73.0 % and the selectivity of 84.0 %, respectively. The isomerization stability of the Ni2P-MCM-41/MOR catalyst was investigated. After the long period test, the catalytic activity of the catalyst could keep good. Based on the study of reaction effect with different test conditions in hydrogen atmosphere, the mechanism of alkane isomerization for Ni2P-MCM-41/MOR catalyst was proposed.

Exploring machine learning applications in chemical production through valorization of biomass, plastics, and petroleum resources: A comprehensive review

Machine learning (ML) is a subtype of artificial intelligence that uses a computer's ability to learn from a given set of accessible data. ML is becoming prominent in almost every business, including the domain of chemical engineering, where there have been numerous researches and investigations. This article provides a detailed overview of the use of ML in the production and characterization study of biomass, polymers, and petroleum products. Categories of ML, including classification, regression, and clustering, are also investigated to get a deeper understanding of ML. From this review, it can be concluded that ML has aided in numerous domains, such as the prediction of biomass energy, the stability of crude oil based on NMR spectroscopy, the calculation of gasoline's octane number, the estimation of fuel oil's kinematic viscosity, the classification of waste plastics, and the estimation of drilling efficiency in petroleum reservoirs, among others. Apart from this, ML has also been playing a significant role in the microwave-assisted pyrolysis of biomass, polymers, and petroleum resources. ML substantially influences chemical engineering and is especially useful for enhancing system efficiency and monitoring processes that are difficult to understand manually. Although several obstacles are associated with ML, such as black box behavior, the need for a large amount of data, and the difficulty of understanding the predictions, deploying the model in the future is uncomplicated once the learning program has been trained.

Experimental and mechanism study on the separation of isobutyl alcohol and water azeotrope using hydrophobic deep eutectic solvents

Isobutyl alcohol with good miscibility, high octane number and energy density has been paid more and more attention in the field of new biofuels, as it is an ideal alternative fuel for gasoline. However, isobutyl alcohol and water azeotrope need a clean and efficient separation method to realize the separation in isobutyl alcohol production process and industrial wastewater. Three hydrophobic deep eutectic solvents (DESs) were used to separate isobutyl alcohol. Decanoic acid was used as hydrogen bond donor and menthol, thymol and lidocaine were used as hydrogen bond acceptors to synthesize DESs. The liquid-liquid equilibrium experiment was carried out for the system containing DESs and MSD −water at 101.3 kPa and 303.15 K, and the separation effect of different DESs was indicated using distribution coefficient (β) and selectivity (S). The σ-Profile can be a good reflection of the strength of a substance's ability to accept and provide hydrogen bonds. The interaction energy and self-diffusion coefficient of the separation system were described quantitatively by molecular dynamics simulation. The relationship between DESs and the separation system was analyzed quantitatively by radial distribution function and spatial distribution function. The separation results show that the three DESs have good separation effect on isobutyl alcohol-water system, among which the DESs synthesized by thymol and decanoic acid has the best separation effect, and the interaction of isobutyl alcohol-water separation process is controlled by van der Waals forces. DESs plays an important role in the separation and treatment of isobutyl alcohol-containing wastewater, and promotes the sustainable development of wastewater treatment projects to save costs and increase production benefits.

Revolutionizing Fuel Efficiency with Optimal Octane Mixtures

Increasing the octane value of fuel can significantly improve engine performance and efficiency. This study explores mixing fuels with different octane ratings to achieve a desired balance of high octane and cost-effectiveness. Fuels with octane numbers 82, 86, 92, and 96 were mixed in various ratios (30%, 50%, 70%) of premium, pertalite, pertamax, and pertamax turbo. Results showed that mixtures like premium and pertalite (octane 85) and premium and pertamax turbo (octane 93) effectively increased octane levels. The study concludes that mixing fuels can enhance octane values and optimize fuel composition for better performance and cost efficiency. Future research could further explore various fuel types and ratios. Highlight: Mixing fuels increases octane rating and engine performance. Optimal fuel composition balances high octane and cost-effectiveness. Significant results with premium and pertamax turbo mixture. Keywoard: Octane Rating, Fuel Mixing, Engine Performance, Fuel Efficiency, Cost-Effective Fuel

Green hydrocarbons and fuels from municipal polymer waste co-fed with natural gas using a batch catalytic slurry process

Landfilled solid waste polymers were converted into high octane green fuels and hydrocarbons by a catalytic depolymerization process. Experiments were conducted in a batch catalytic reactor pressurized with methane as a co-feed. Design of Experiments (DOE) methodology was used for process optimization and parametric study. The operating conditions that maximize the liquids aromatic hydrocarbons were found using response optimizer tool. The reaction temperature and polymer to catalyst ratio (PCR) were found to have significant effects on the responses and methane pressure was not significant for yields of solids, liquids and gaseous products. However, pressurized methane facilitated dehydrocyclization reactions resulting in increased monoaromatic hydrocarbons in the final liquid products. Experiments conducted with methane feed at optimized reaction conditions resulted in 89% aromatic hydrocarbons, 8% paraffins and about 3% other hydrocarbons in liquid products. Aromatic products included benzene (6.5%), toluene (25%), xylenes (27%), ethylbenzene (4.5%), other monoaromatics (22%) and polyaromatic hydrocarbons (4%). Gaseous products contained propylene (47%) and hydrogen (23.9%). The utilization of waste polymers as feedstock materials, flare gas (methane) as a co-feed, and zeolite catalysts makes this batch zeolitic slurry process greener, resulting in green hydrocarbons and green fuels.

Upcycling of polyethylene to gasoline through a self-supplied hydrogen strategy in a layered self-pillared zeolite

Conversion of plastic wastes to valuable carbon resources without using noble metal catalysts or external hydrogen remains a challenging task. Here we report a layered self-pillared zeolite that enables the conversion of polyethylene to gasoline with a remarkable selectivity of 99% and yields of >80% in 4 h at 240 °C. The liquid product is primarily composed of branched alkanes (selectivity of 72%), affording a high research octane number of 88.0 that is comparable to commercial gasoline (86.6). In situ inelastic neutron scattering, small-angle neutron scattering, solid-state nuclear magnetic resonance, X-ray absorption spectroscopy and isotope-labelling experiments reveal that the activation of polyethylene is promoted by the open framework tri-coordinated Al sites of the zeolite, followed by β-scission and isomerization on Brönsted acids sites, accompanied by hydride transfer over open framework tri-coordinated Al sites through a self-supplied hydrogen pathway to yield selectivity to branched alkanes. This study shows the potential of layered zeolite materials in enabling the upcycling of plastic wastes.

Combustion of gasoline with oxygen-containing and nano-additives: An experimental study, modeling, optimization, and analysis survey

BackgroundPollutants emitted from fuel combustion have become a global concern, prompting researchers to explore solutions like fuel formulation modification. MethodsThis study delved into enhancing gasoline fuel performance and octane number by incorporating varying proportions of 2-methyl-1-propanol, bioethanol, MTBE additives, tert‑butanol, and nanoparticles (ZnO, ZrO2, and CNT). These compositions underwent assessment at different engine loads and speeds. Vapor pressure, a fundamental property of gasoline that signifies its volatility, was examined. Despite the utilization of diverse additives and enhancers, their impact on vapor pressure was minimal at relatively low concentrations. Significant findingsAs a result, flash point, octane number, and engine performance were evaluated for the developed fuels. The findings unveiled improved engine performance coupled with reduced emissions. The octane number demonstrated enhancement, approaching gasoline's, while the combustion point remained similar. Notably, pollutant levels exhibited significant reduction.When comparing gasoline fuel at an engine speed of 1500 RPM and a throttle opening of 30 % with gasoline mixed with 2-methyl-1-propanol alcohol, MTBE, and zirconium dioxide under identical conditions, the results showed a reduction of 82.8 % in carbon monoxide emissions, carbon dioxide decreased by 54.05 %, unburnt hydrocarbons decreased approximately by 42.42 %, nitrogen oxides reduced by 22.97 %, engine power increased by 0.5 %, torque increased up to 164 %, and the octane number increased by 7.03 %.

Qualitative assessment of regular and premium gasoline available in Bangladesh markets

Assessing the quality of fuel is essential to comprehend its impact on the environment and human health. In this study, the evaluation of fuel quality standards at the consumer level was conducted by analyzing the motor fuels in Khulna, Bangladesh. A total of 32 samples of petrol (regular gasoline), and octane (premium gasoline) were collected from the fuel stations in the Khulna City Corporation area and analyzed with an FTIR-Fuel Analyzer. Fuel properties, such as research octane number (RON), motor octane number (MON), ethanol content, olefins content, and oxygen content were analyzed. For petrol, the average RON, MON, olefins, and oxygen content were 95.34, 85.70, 8.23 %v/v, and 0.78 %m/m, respectively, and for octane, they were 96.96, 85.39, 1.25 %v/v, and 0.09 %m/m, respectively. Almost all of these parameters complied with both Bangladesh standard and Euro 5 fuel specifications, and those that did not comply were very close to their standard values. However, benzene concentration, which was not specified in Bangladesh Standard, was the most alarming metric for octane since none of the samples matched the Euro 5 fuel specifications of the maximum concentration of 1 %v/v benzene; on average it was 3.70 %v/v. Although petrol benzene content (average 1.50 %v/v) was not as bad as it was for octane, it was still nowhere near good enough, with only 25% of the samples within the recommended level among the studied sample. This information holds significance in establishing the fuel profile and facilitating the identification of distinct samples linked to adulteration. Therefore, the analysis of motor fuel qualities is essential for maintaining the environment, human health, and the economy of a country.

Региональный компонент содержания образования: нефтехимическое производство

Studying the scientific foundations of modern production, including petrochemical production, in secondary school is one of the most important means to solve the problem of polytechnic training of students. The research lesson and its content are aimed at studying the production of gasoline, predicting the chemical processes of increasing the octane number of gasoline.

EXPERIMENTAL DETERMINATION OF ADDING CELLULOSE NITRATE TO THE OCTANIC NUMBER OF FUELS

The paperwork has as purpose improvement of anti-explosive properties of liquid fuels for spark ignition engines through nitrate addition and quantitative determination of the octane number resulting from the CFR ASTM Waukesha engine support.

Marine benthic diatom Psammodictyon panduriforme (MACC 35) as a potent producer of long chain hydrocarbons and fatty acids of biofuel significance

Marine diatoms are promising feedstock for biofuel industries as a source of hydrocarbons and fatty acids. In the present study, eleven marine diatom isolates from the west coast of India were analysed for hydrocarbons and lipids. The comparative analyses indicated that Psammodictyon panduriforme (MACC 35), a diatom isolate from the water samples collected from 1000 m depth, with a hydrocarbon yield of 37.27 mg g−1 L−1 and 2.1 % of the total biomass of 0.56 gL−1 was a promising species followed by Biddulphia sp. (MACC 6) with hydrocarbon yield of 25.4 mg g−1 L−1 and 1.3 % of the total biomass of 0.48 g L−1. Hydrocarbon analyses by gas chromatography with high resolution mass spectrometry (GCMS) showed that the long chain hydrocarbons found in the majority of the marine diatoms were undecane 4,7 dimethyl, hexadecane, octadecane,3-ethyl-5-(2-ethyl-butyl), tetradecane, tetracosane, eicosane-2 methyl, heptacosaneand hexacosane. The fatty acid profile showed the presence of stearic acid, 9-octadecenoic acid, myristic acid, palmitic acid, and arachidic acid with excellent biodiesel properties. Hydrocarbons of high fuel quality can be produced by optimizing hydrocarbon production in the potent marine diatom Psammodictyon panduriforme and catalytic cracking of long chain hydrocarbons to short chain alkanes with high octane ratings.